Gartner, Forrester, and IDC All Agree: In a World of AI and Machine Learning, Data Quality is Cool


Gartner just recently published its Cool Vendors in AI for Supply Chain report, recognizing ClearMetal as a leading supply chain visibility provider for its AI and machine learning capabilities. Ironically, it wasn’t predictive analytics or end-to-end visibility capabilities that garnered the accolades; rather, it was the work ClearMetal is doing to solve the supply chain “data problem” that caught the analysts’ eyes. With all the hype around the advanced capabilities of today's technologies, it's eye-opening to see that real innovation lies in using such technologies to solve rudimentary problems like access to data and data quality. 


Redefining Cool

Have a look at an agenda from any recent supply chain event, such as Gartner's Supply Chain Conference or the Eye for Transport (EFT) summit, and you'll find them loaded with terms like:

  • Digital Transformation

  • End-to-end visibility

  • Advanced analytics

  • Blockchain

These buzzwords grab headlines and attract attendees, but as the emerging tech hype boils on, there's a low-key narrative that's been slowly simmering in the supply chain community regarding a topic that's been overlooked and undervalued for years: data reliability.

A growing voice in the industry is calling for greater attention to underlying supply chain data to successfully feed the major transformation initiatives being visualized at the C-level. Three of the major analyst firms have called out this need.    

The Importance of Data

Boris Evelson, Vice President and Principal Analyst at Forrester Research, told CIO Magazine recently that before advanced analytics and machine learning can be applied to supply chain data, companies must first collect and organize that data, coming in from various partners. 

Getting data from all these sources, that’s the big challenge,” Evelson said. But that collected data is not immediately usable. “A supplier might have data at one level of detail, and a distributor might have it at a different level of detail. A supplier might have data on an individual product, but the distributor might only have data based on the container.

— Boris Evelson, Forrester Research VP


IDC's, John Santagate, published a paper last year on predictive logistics in which he called out that data cleanliness, reliability and availability are major challenges.

Data silos are often a challenge as companies struggle to find a single source of the truth.... Given the historical struggles to transform data into actionable intelligence, as manufacturers look to adopt new technology, they must have a detailed plan for data and analytics and how to provide business insights.

— John Santagate, IDC Research Director


Just recently, Gartner published its Cool Vendors in AI for Supply Chain report, in which it recognized ClearMetal specifically for the work it's doing to solve the data problem. 

Traditional applied analytics and visibility software platforms were compromised by not being able to streamline or hone in high-quality, grouped source datasets (which in turn provided optimal pathways for accelerated machine learning and broader applications of AI techniques) ...

— Andrew Stevens, Gartner Supply Chain Research Director


There are many applications and approaches to digital transformation, but in the end, it's about businesses transforming their supply chains with data - gaining better access to data, making sense of data, and using that data in a fundamentally different way to drive profitability.

As ClearMetal CEO Adam Compain recently told a room full of supply chain leaders at the American Supply Chain Summit:

It is impossible to get end-to-end visibility unless you’re solving the underlying data problem. Only when you are able to solve that underlying data problem can you make not only better, but fundamentally different decisions.

— Adam Compain, ClearMetal CEO


This message continues to gather momentum in the analyst community. And it’s beginning to pick up within the halls of supply chain organizations all over the world.

Click here to learn more about how retailers, manufacturers and 3PLs are setting the stage for supply chain visibility, predictability and transformation by first solving the underlying data problem.


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